Senior Principal, Data Engineering

Role Summary

The Senior Principal will be responsible for leading projects related to data engineering requirements and initiatives across Jazz Research and Development. The Senior Principal will lead data projects from across the business including Clinical, Pre-Clinical, Non-Clinical, Chemistry, RWD and Omics.

• Lead the design, development and maintenance of data pipelines for processing Research and Development data from diverse sources (Clinical Trials, Medical Devices, Pre-Clinical, Omics, Real World Data) utilizing the AWS technology platform.
• Create and optimize ETL/ELT processes for structured and unstructured data using Python, R, SQL, AWS services and other tools.
• Build and maintain data repositories using AWS S3 and FSx technologies. Establish data warehousing solutions using Amazon Redshift.
• Build and maintain standard data models.
• Own data quality frameworks, validation processes and KPIs to ensure accuracy and consistency of data pipelines.
• Implement data versioning and lineage tracking to support data traceability, regulatory compliance and audit requirements.
• Create and maintain documentation for data processes, architectures, and workflows.
• Implement modern software development best practices (e.g. Code Versioning, Dev Ops, CD/CI).
• Support collaboration with RnD Researchers, Data scientists and Stakeholders to understand data requirements and deliver appropriate solutions in a global working model.
• Maintain compliance with data privacy regulations such as HIPAA, GDPR
• May be required to develop, deliver or support data literacy training across R&D.

• Expert knowledge of data engineering tools such as Python, R and SQL for data processing.
• Expert proficiency with AWS services particularly S3, Redshift, FSx, Glue, Lambda.
• Expert proficiency with relational databases.
• Strong background in data modeling and database design.
• Strong knowledge with unstructured database technologies (e.g. No
  
  SQL) and other database types (e.g. Graph).
• Experience with Containerization such as Docker and EKS/Kubernetes.
• Experience with one or more RnD research process and associated regulatory requirements.
• Exposure to healthcare data standards (CDISC, HL7, FHIR, SNOMED CT, OMOP, DICOM).
• Experience to big data technologies and handling.
• Knowledge of machine learning operations (MLOps) and model deployment.
• Strong problem-solving and analytical abilities.
• Excellent communication skills for collaborating with stakeholders.
• Experience working in an Agile development environment.

• Bachelor’s Degree in Computer Science, Statistics, Mathematics, Life Sciences, or other relevant scientific fields;
  Master’s Degree preferred
• 5-7 years of experience in data engineering, with at least 2 years focusing on healthcare, research or clinical related data

• Occasional mobility within office environment
• Routinely sitting for extended periods of time
• Constantly operating a computer, printer, telephone and other similar office machinery